Comparison
Chunking vs Recursive Chunking
Chunking and Recursive Chunking are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Chunking
Always — chunking is upstream of every other RAG decision. Spending 2 hours on chunking strategy commonly beats 2 weeks of prompt tuning.
A 50-page PDF split into 200-token chunks with 50-token overlap → ~150 chunks indexed.
When you would reach for Recursive Chunking
Recursive Chunking comes up when the question is fundamentally about agents & tools.
A 5000-character article: recursive splitter at 1000 chars with 100-char overlap → 6 chunks, each ending on a natural sentence boundary.
Frequently asked
What is the difference between Chunking and Recursive Chunking?
Chunking: Chunking is the process of splitting source documents into smaller passages before embedding them for retrieval. Chunk size and boundaries control how relevant retrievals will be. Recursive Chunking: Recursive chunking splits text by trying progressively smaller separators — paragraphs, then sentences, then words — until each chunk fits the target size, preserving natural boundaries where possible.
When should I use Chunking vs Recursive Chunking?
Always — chunking is upstream of every other RAG decision. Spending 2 hours on chunking strategy commonly beats 2 weeks of prompt tuning. Recursive Chunking applies when you are focused on agents & tools.
Are Chunking and Recursive Chunking the same thing?
No. Chunking is agents & tools; Recursive Chunking is agents & tools. They are related but address different parts of the AI stack.